Lead Software Engineer - Java, AWS, Kafka, Apache Flink

As a Lead Software Engineer at JPMorganChase within the Consumer and Community Banking, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firms business objectives.

Job responsibilities

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
• Develops secure high-quality production code, and reviews and debugs code written by others
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
• Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Proficiency in back-end technologies (e.g., Java, Springboot, Node.js ) with experience building microservices-based applications for full-stack roles, proficiency also includes front-end technologies (e.g., HTML, CSS, JavaScript, Typescript, React, Angular).
• Demonstrated ability to independently solve design and functionality challenges with minimal supervision.
• Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON.
• Hands-on experience designing and building scalable applications using SQL and NoSQL databases.
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations experience coaching engineers on safe, compliant adoption within delivery practices
• Proficient in all aspects of the Software Development Life Cycle including advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• Led design and delivery ofKafka-based event streamingplatforms/services inhigh-throughput (high TPS)environments deep experience withevent-driven architecturepatterns and distributed systems reliability. Proven ability tolead technical direction: drive architecture decisions, write/own design docs, align stakeholders, and deliver through ambiguity.
• Experience improvingoperability(SLOs/SLAs, on-call readiness, monitoring, incident response, postmortems) for streaming systems. Hands-on experience building and operatinghigh-volume data processing pipelinesusingApache Spark (Spark SQL, Structured Streaming)and/orApache Flink(DataStream/Table API) in production.